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Record W2594507218 · doi:10.1093/biolreprod/85.s1.343

Reproductive Steroid Hormones Alter Ovarian Cancer Progression in Mouse Models.

2011· article· en· W2594507218 on OpenAlexaff
Kendra Hodgkinson, Laura A. Laviolette, Carolina Perez‐Iratxeta, Barbara C. Vanderhyden

Bibliographic record

VenueBiology of Reproduction · 2011
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsOntario GenomicsOttawa Regional Cancer Foundation
Fundersnot available
KeywordsOvarian cancerMenopauseEstrogenBiologyInternal medicineEndocrinologyHormoneCancerOvaryCancer researchMedicine

Abstract

fetched live from OpenAlex

Epidemiological studies have shown that estrogen replacement after menopause increases the risk of developing ovarian cancer, whereas taking oral contraceptives before menopause decreases that risk. Because the majority of ovarian cancers are diagnosed after menopause, and because so many women are exposed to exogenous hormones, it is important to understand how menopause and hormones alter cancer progression. To study the early stages of ovarian cancer, we generated a transgenic mouse model of ovarian cancer that we are now using to determine how steroid hormones and menopausal changes in ovarian phenotype alter disease progression. We hypothesized 1) that estrogen would stimulate cancer progression by altering transcription of genes involved in proliferation, metastasis and angiogenesis and 2) that menopausal ovaries would be more sensitive to exogenous hormone action. In the tgCAG-LS-TAg mouse model, SV40 T antigen is activated, and therefore tumourigenesis is selectively induced, in the ovarian surface epithelium, a primary site of origin for ovarian cancers. T antigen expression was induced in young (3 months) or older mice (8 months) by intrabursal injection of adenovirus expressing Cre recombinase. To model ovarian cancer in a menopausal ovary, we simulated 'menopause' by injecting vinylcyclohexene diepoxide 2 months prior to tumour initiation. Mice were then treated with 60-day pellets releasing 17beta-estradiol (E2), progesterone (P4), or both E2 and P4, and were monitored until a loss of wellness endpoint. Median survival after adenovirus injection tended to be shorter in young (113 days, range of 75-181) vs. older mice (142 days, range of 53-207). The induction of 'menopause' had no effect on survival, but altered tumour histology relative to non-'menopausal' mice. In both age groups, treatment with E2 decreased median survival by 56-68% relative to controls. To differentiate between E2 effects on tumour initiation vs. progression and to investigate the mechanisms underlying the decreased survival caused by E2, we used a xenograft model in which SCID mice were injected with ovarian cancer cells derived from the ascites of a tgCAG-LS-TAg mouse treated with E2 (MASE) or control pellets (MASC). E2 decreased median survival time for both groups, but caused more rapid progression in mice injected with MASE (32 days) compared to MASC cells (48.5 days). Western blotting showed that estrogen receptor (ERα levels were 5-fold higher in the MASE than in the MASC cells, suggesting that increased ERα levels in the MASE cells are responsible for the enhanced responses to E2. Microarray analysis of MASE tumours from mice treated with exogenous E2 showed upregulation of 197 genes and downregulation of 55 genes compared to tumours from placebo-treated mice. In addition to several known ER targets such as Pgr, several novel genes were identified, including genes involved in angiogenesis, cell proliferation and differentiation. These are currently being validated and tested for functional significance. In summary, our results indicate that overall survival is not altered by ovarian pre/post-menopausal status, and that E2 accelerates ovarian cancer progression in both young and older mice. Further characterization of the function of E2-targeted genes will aid the identification of mechanisms by which this hormone increases the risk of ovarian cancer. (poster)

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.322
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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